Last Observation Carried Forward In a data frame? [duplicate]

I wish to implement a "Last Observation Carried Forward" for a data set I am working on which has missing values at the end of it.

Here is a simple code to do it (question after it):

LOCF <- function(x)
{
    # Last Observation Carried Forward (for a left to right series)
    LOCF <- max(which(!is.na(x))) # the location of the Last Observation to Carry Forward
    x[LOCF:length(x)] <- x[LOCF]
    return(x)
}


# example:
LOCF(c(1,2,3,4,NA,NA))
LOCF(c(1,NA,3,4,NA,NA))

Now this works great for simple vectors. But if I where to try and use it on a data frame:

a <- data.frame(rep("a",4), 1:4,1:4, c(1,NA,NA,NA))
a
t(apply(a, 1, LOCF)) # will make a mess

It will turn my data frame into a character matrix.

Can you think of a way to do LOCF on a data.frame, without turning it into a matrix? (I could use loops and such to correct the mess, but would love for a more elegant solution)

Solution 1:

This already exists:

library(zoo)
na.locf(data.frame(rep("a",4), 1:4,1:4, c(1,NA,NA,NA)))

Solution 2:

If you do not want to load a big package like zoo just for the na.locf function, here is a short solution which also works if there are some leading NAs in the input vector.

na.locf <- function(x) {
  v <- !is.na(x)
  c(NA, x[v])[cumsum(v)+1]
}

Solution 3:

Adding the new tidyr::fill() function for carrying forward the last observation in a column to fill in NAs:

a <- data.frame(col1 = rep("a",4), col2 = 1:4, 
                col3 = 1:4, col4 = c(1,NA,NA,NA))
a
#   col1 col2 col3 col4
# 1    a    1    1    1
# 2    a    2    2   NA
# 3    a    3    3   NA
# 4    a    4    4   NA

a %>% tidyr::fill(col4)
#   col1 col2 col3 col4
# 1    a    1    1    1
# 2    a    2    2    1
# 3    a    3    3    1
# 4    a    4    4    1